The escalating conflict between cetaceans and fisheries underscores the need for efficient mitigation strategies that balance conservation priorities with economic viability. This study presents a TinyML-driven approach deploying an optimized Convolu...
Convolutional neural networks (CNNs) are used for classification, as they can extract complex features from input data. The training and inference of these networks typically require platforms with CPUs and GPUs. To execute the forward propagation of...
One of the most challenging aspects of agricultural pest control is accurate detection of insects in crops. Inadequate control measures for insect pests can seriously impact the production of corn and soybean plantations. In recent years, artificial...
Medical imaging plays a pivotal role in diagnostic medicine with technologies like Magnetic Resonance Imagining (MRI), Computed Tomography (CT), Positron Emission Tomography (PET), and ultrasound scans being widely used to assist radiologists and med...
Breast cancer (BC) mortality rates remain high in Low- and Middle-Income Countries (LMICs) due to limited awareness, poverty, and inadequate medical facilities that hinder early detection. Although deep learning models have achieved high accuracy in...
This research addresses the optimization and deployment of convolutional neural networks for eyeglasses detection on low-power edge devices. Multiple convolutional neural network architectures were trained and evaluated using the FFHQ dataset, which...
Advanced driver-assistance systems (ADASs) combine real-time sensing, computer vision, and embedded artificial intelligence to increase road safety. This study presents a state-driven, multi-functional ADAS architecture intended for eventual deployme...
Deep learning-based object detection technology can efficiently infer results by utilizing graphics processing units (GPU). However, when using general deep learning frameworks in embedded systems and mobile devices, processing functionality is limit...
14 November 2026
Inspired by the hierarchical, receptive-field-based processing of biological vision and by synaptic pruning in the developing brain, this work proposes a bio-inspired optimized convolutional neural network framework for multi-class cancer classificat...
Real-time trajectory forecasting for curling stones is essential for on-ice decision support, yet prior work often emphasizes offline analysis, fixed-window predictors, or physics-driven models that require additional measurements, and it rarely repo...
This paper presents an assistive smartphone interaction system that combines mobile gaze tracking with EEG-based BCI commands. The Android application estimates the user’s gaze with the front camera, MediaPipe facial landmarks, a TinyTrackerS T...
The response time of Artificial Neural Network (ANN) inference is critical in embedded systems processing sensor data close to the source. This is particularly important in applications such as predictive maintenance, which rely on timely state chang...
Background: Type 1 Diabetes Mellitus (T1D) is an autoimmune disease that can cause serious complications that can be avoided by preventing the glycemic levels from exceeding the physiological range. Straightforwardly, many data-driven models were dev...
Image aesthetics processing (IAP) is used primarily to enhance the aesthetic quality of images. However, IAP faces several issues, including its failure to analyze the influence of visual scene information and the difficulty of deploying IAP capabili...
Cardiovascular diseases impose a substantial global health burden and often require timely detection, creating strong demand for real-time electrocardiogram (ECG) monitoring on resource-constrained devices. Although portable single-lead wearable ECG...
Background: This study presents a real-time mobile system for identifying mixed and partly covered foreign coins and banknotes using the You Only Look Once version 11 (YOLOv11) deep learning framework. The proposed system addresses practical challeng...
In today’s digital world, and in light of the growing pandemic, many yoga instructors opt to teach online. However, even after learning or being trained by the best sources available, such as videos, blogs, journals, or essays, there is no live...
This paper aims to explore the possibility of utilizing vision transformers (ViTs) for on-edge medical diagnostics by experimenting with the Kvasir-Capsule image classification dataset, a large-scale image dataset of gastrointestinal diseases. Quanti...
Major depressive disorder requires scalable, low-burden screening tools. We examined whether three-channel resting-state EEG can support reliable discrimination between major depressive disorder and healthy controls using a lightweight model compatib...
Neurodegenerative diseases (NDDs), including Parkinson’s disease (PARK), Huntington’s disease (HUNT), and amyotrophic lateral sclerosis (ALS), are associated with characteristic gait alterations. This study proposes an image-based deep-le...
Autonomous warehouse drones require detection that is both accurate and spatially selective, detecting only the labels directly in front of the drone and ignoring those on neighbouring racks. Standard YOLOv8n has no built-in awareness of absolute pix...